Support vector machine accuracy improvement with classification
Rapid increase in the information technology through digitalization, leads to fast
enhancement in technical industry has expanded the need for effective data mining. Data …
enhancement in technical industry has expanded the need for effective data mining. Data …
[PDF][PDF] Improving signal detection accuracy at FC of a CRN using machine learning and fuzzy rules
The performance of a cognitive radio network (CRN) mainly depends on the faithful signal
detection at fusion center (FC). In this paper, the concept of weighted fuzzy rule in Iris data …
detection at fusion center (FC). In this paper, the concept of weighted fuzzy rule in Iris data …
A New Preprocessing Method for Diabetes and Biomedical Data Classification
S CHALO, İB AYDİLEK - Qubahan Academic Journal, 2022 - journal.qubahan.com
People of all ages and socioeconomic levels, all over the world, are being diagnosed with
type 2 diabetes at rates that are higher than they have ever been. It is possible for it to be the …
type 2 diabetes at rates that are higher than they have ever been. It is possible for it to be the …
Using Intuitionistic Fuzzy Set to Classify Uncertain and Linearly Non-Separable Data
S Abdulla - Journal of Computer Science and Technology …, 2024 - al-kindipublisher.com
The problem of non-linearly separable data points requires more efforts to classify the data
sample with high accuracy. This paper proposes a new classification approach that employs …
sample with high accuracy. This paper proposes a new classification approach that employs …
A hybridized levy flight fruit fly optimization based kernel extreme learning machine for biomedical data classification
The main motive behind classification is to map an input feature space to a predefined class
labels in high dimensional microarray data sets to enhance the classification accuracy and …
labels in high dimensional microarray data sets to enhance the classification accuracy and …
A hybridized adaptive fruit fly optimization based online sequential extreme learning machine for bio-medical data classification
The objective of classification in high dimensional biomedical data is to map an input feature
space to a predefined class labels with higher classification accuracy and less …
space to a predefined class labels with higher classification accuracy and less …
Optimized Support Vector Regression for Predicting Leishmaniasis Incidences
N Frissou, MT Kimour, S Selmane - Informatica, 2021 - informatica.si
Abstract Support Vector Regression (SVR) is a new approach in machine learning for time
series prediction showing good performance. A big challenge for achieving optimal …
series prediction showing good performance. A big challenge for achieving optimal …
Low-complexity sound event classification based on graph signal in noisy environments
Y Liu, Y Wei - 2019 12th International Congress on Image and …, 2019 - ieeexplore.ieee.org
To solve the problem of high computational cost in sound event classification using graph
signal, in this paper, a low complexity algorithm based on dynamic selection of Time …
signal, in this paper, a low complexity algorithm based on dynamic selection of Time …
A Fruit Fly Optimization-Based Extreme Learning Machine for Biomedical Data Classification
In high-dimensional biomedical datasets, the main objective is to map an input feature
space to a predetermined class labels with less execution time and with high classification …
space to a predetermined class labels with less execution time and with high classification …
Sécurité Des Données Biomédicales Echangées en Télémédecine
A KHALDI, H BEN CHEIKH, K BOUZAINE - dspace.univ-ouargla.dz
La télémédecine s' appuie sur une infrastructure d'échange d'informations numériques. Bien
que les progrès récents des technologies de l'information offrent de nouvelles façons …
que les progrès récents des technologies de l'information offrent de nouvelles façons …